328. The Basedow’s disease radiometabolic therapy: The uptake volume estimation

In pelvic bone SPECT using Tc-99m labeled compounds, physical effects such as nonhomogeneous attenuation and the accumulation of activity into the bladder during the data acquisition process can often result in data inconsistencies. With filtered backprojection (FBP) reconstruction, this may result in streak artifacts. Various methods for attenuation compensation can be employed to account for some of these streaks, but if the rate of uptake of tracer in to the bladder is sufficient, the resultant streaks may be significant enough to impair lesion detection. We have investigated various reconstruction methods in an effort to reduce these artifacts. In order to assess the impact of inconsistent bladder activities on the detection of pelvic lesions, SPECT imaging was simulated using the Zubal voxelized phantom, for cases of both a static bladder activity and a changing activity distribution. Reconstructions were performed using FBP, ordered subset-expectation maximization (OSEM) and dynamic expectation maximization (dEM) and was assessed for lesion detectability using a channelized, nonprewhitening (CNPW) numerical observer model. This observer model was used to optimize reconstruction strategies for a human LROC observer study. The human LROC observer study was performed in order to assess the various reconstruction methods in terms of lesion detectability. Three human observers were used in this test. The results of this test indicate that FBP performs significantly worse than static OSEM iterative reconstruction with attenuation correction when assessed using the area under the LROC curve (maximal ALROC=0.47 for FBP versus 0.71 for OSEM). Visually, the dEM algorithm produces images with slightly reduced streak artifacts compared to OSEM, but this improvement was not reflected in significantly improved ALROC values. In fact, when assessed using human LROC methodology, detectability actually decreased slightly when using dEM (maximal ALROC=0.71 for OSEM versus 0.66 for dEM), although this reduction was not determined to be statistically significant. It is possible that the slightly reduced performance of the dEM algorithm may be due, in part, to not performing an optimization in the number of reconstruction iterations as was performed for the OSEM method

BackgroundPositron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone.Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT.MethodsExperiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images.ResultsThe most important finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images.ConclusionThe combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

This work is aimed at evaluating the image reconstruction techniques used in single photon emission computed tomography (SPECT/CT) imaging. The reconstruction techniques considered in this work are: the ordered subset expectation maximization (OSEM) and the Filtered Back Projection (FBP). An anthropomorphic torso phantom with lung and liver inserts was injected with 99mTc. The liver and the background were given 0.2 MBq/ml and 0.07 MBq/ml respectively. The lungs inserts were filled with polystyrene beads for humanization. A mimicked 30 ml tumor (27 mm) in the liver insert was given 2 MBq/ml sequential SPECT/CT (step and shot, 10 mins over 180° per head) and CT (120 kVp, 80 mAs) projections were acquired using dual head SPECT/16 slice CT system. The projections were reconstructed using OSEM (10 subsets for 2–10 numbers of iterations, Butterworth post filtering, 10 orders and 0.48 frequencies) and FBP (using Butterworth post filtering at 10 order and cutoff frequencies of 0.38–0.58, 0.05 gaps). Image J software was used for the image analysis. Statistical t-test tested the mean gray values of the tumor and its background. The OSEM and FBP reconstructed images were evaluated from their contrast-to-noise ratio (CNR). The optimal parameter was selected based on 3–5 CNR detection range set by the Rose criterion. The t-test showed the background and the tumors mean values to be statistically significant (P ≪ 0.05). The CNR values for FBP images were all below the detection range, maximum value at the cutoff frequency 0.48 (1.69). In OSEM images at cutoff frequency 0.48, the CNR values were within the detection range for 2–8 numbers of iteration with maximum value (4.89) at 4 numbers of iteration. OSEM was found to be the best for tumor detection and administered activity can be reduced at 4 OSEM’s of iterations (40 MLEM iterations) for patient safety. Keywords: Anthropomorphic torso phantom, 99mTc, SPECT, iterative reconstruction, CNR, P-Value, liver Cite this Article F. Usman, R. Zainon, A. Saidu, A. Bala. Evaluation of image reconstruction techniques in Single photon emission computed tomography (SPECT/CT) imaging. Research & Reviews: Journal of Physics. 2016; 5(2): 13–22p.

Objective To study the effect of the reconstruction method on the semi-quantitative distribution of dopamine transporter (DAT) in the brain, 2β-carbomethoxy-3β-(4-fluorophe-nyl)-(N-11C-methyl)tropane (11C-CFT) PET images of healthy subjects were reconstructed by different PET reconstruction methods. Methods From March 2014 to June 2015, the 11C-CFT PET images of 41 healthy subjects were reconstructed by filtering back projection(FBP) method and ordered subsets expectation maximization (OSEM) iterative method. The brain regions of interest (ROI), namely, caudate nucleus, anterior putamen, and posterior shell nucleus, were automatically sketched with the parietal and occipital cortex lacking of DAT distribution as reference regions. The semi-quantitative value of DAT distribution was calculated using the following formula: radioactivity count of ROI/radioactivity count of parietal and occipital cortex-1. Paired t-test was used to compare the semi-quantitative values of DAT distribution. Correlation analysis was performed using the Pearson correlation analysis. Results The values of DAT distribution based on OSEM were as follows: caudate nucleus (1.77-2.15), anterior putamen (2.17-2.39), and posterior putamen (1.71-2.06). The values of DAT distribution based on FBP were as follows: caudate nucleus (1.68-2.10), anterior putamen (2.07-2.37), and posterior putamen (1.62-1.96). In the bilateral caudate nucleus and anterior and posterior putamen, the 11C-CFT of DAT distribution by OSEM was significantly higher than that by FBP(t=9.658-15.859, all P=0.000). The Pearson correlation analysis showed that the semi-quantitative values of DAT distribution by FBP and OSEM were positively correlated with each other in the bilateral caudate nucleus and anterior and posterior putamen (R2=0.907-0.951, all P=0.000). The DAT distribution by OSEM and FBP decreased with aging in the caudate nucleus and anterior and posterior putamen. Conclusions A significant difference was found in the semi-quantitative value of the DAT distribution in the brain of healthy subjects by different PET reconstruction methods. Therefore, a consistent PET image reconstruction method should be used in a multicenter or longitudinal study. Key words: Dopamine plasma membrane transport proteins; Positron-emission tomography; Filtered backprojection; Iterative

The Siemens Biograph TruePoint TrueV (B-TPTV) positron emission tomography (PET) scanner performs 3D PET reconstruction using a system matrix with point spread function (PSF) modeling (called the True X reconstruction). PET resolution was dramatically improved with the True X method. In this study, we assessed the spatial resolution and image quality on a B-TPTV PET scanner. In addition, we assessed the feasibility of animal imaging with a B-TPTV PET and compared it with a microPET R4 scanner. Spatial resolution was measured at center and at 8 cm offset from the center in transverse plane with warm background activity. True X, ordered subset expectation maximization (OSEM) without PSF modeling, and filtered back-projection (FBP) reconstruction methods were used. Percent contrast (% contrast) and percent background variability (% BV) were assessed according to NEMA NU2-2007. The recovery coefficient (RC), non-uniformity, spill-over ratio (SOR), and PET imaging of the Micro Deluxe Phantom were assessed to compare image quality of B-TPTV PET with that of the microPET R4. When True X reconstruction was used, spatial resolution was <3.65 mm with warm background activity. % contrast and % BV with True X reconstruction were higher than those with the OSEM reconstruction algorithm without PSF modeling. In addition, the RC with True X reconstruction was higher than that with the FBP method and the OSEM without PSF modeling method on the microPET R4. The non-uniformity with True X reconstruction was higher than that with FBP and OSEM without PSF modeling on microPET R4. SOR with True X reconstruction was better than that with FBP or OSEM without PSF modeling on the microPET R4. This study assessed the performance of the True X reconstruction. Spatial resolution with True X reconstruction was improved by 45 % and its % contrast was significantly improved compared to those with the conventional OSEM without PSF modeling reconstruction algorithm. The noise level was higher than that with the other reconstruction algorithm. Therefore, True X reconstruction should be used with caution when quantifying PET data.

In this study, we developed a detector’s eye view (DEV)-based ordered subsets expectation maximization (OSEM) algorithm for more accurate reconstruction of benchtop x-ray fluorescence computed tomography (XFCT) images. The proposed approach was tested using two sets of benchtop XFCT imaging data derived from a newly performed gold nanoparticle (GNP)-containing phantom imaging study and a previously published postmortem benchtop XFCT imaging study of a tumor-bearing mouse injected with GNPs. DEV-based OSEM resulted in higher spatial resolution (up to ~20% decrease in the full width at half maximum values of the regions of interest), compared with filtered back-projection (FBP) and traditional OSEM. It also resulted in up to an order of magnitude smaller background noise in the reconstructed images than FBP, while producing consistently less background noise than traditional OSEM.

We have previously developed a model-based method to compensate for the crosstalk in simultaneous acquisition of Tc-99m stress and Tl-201 rest myocardial perfusion SPECT. The purpose of this study is to evaluate the performance of this method in terms of a defect detection task using a mathematical Channelized Hoteling Observer (CHO) study. In this study we also optimized the iteration number in reconstruction of Tl distributions. A population of male and female NCAT phantoms were used to realistically model variation in patients. Both defect-free and defect-present data of Tc and Tl were simulated using the SimSET/PHG codes and our newly developed and validated angular response function (ARF) method to mimic simultaneous acquisition and separate acquisition. Poisson noise was modeled at clinically realistic levels. The Tl data were reconstructed using filtered backprojection (FBP) and ordered subset expectation maximization (OSEM) algorithms for up to 20 iterations with and without the model-based crosstalk compensation (MBC). CHO methodology and receiver operating characteristic (ROC) analysis were applied to short axis Tl images to obtain ROC curves and area under ROC curves (AUC). The AUC values were compared with those from separately acquired data reconstructed using FBP and OSEM algorithms. The results show that a relatively small number of iteration (/spl sim/3) is optimal for the postreconstruction filtering cutoff frequency of 0.16 pixel/sup -1/ used in this study. Also, the AUC values obtained with the MBC were significantly better than those without crosstalk compensation and those with the FBP reconstruction method applied to the separately acquired data.

Introduction: PET/CT and PET/MRI are valuable multimodality imaging techniques for visualizing both functional and anatomical information. The most used PET reconstruction algorithm is Ordered Subset Expectation Maximization (OSEM). In OSEM, the image noise increases with increased number of iterations, and the reconstruction needs to be stopped before complete convergence. The Bayesian penalized likelihood (BPL) algorithm, recently introduced, uses a noise penalty factor (β) to achieve full convergence while controlling noise. This study aims to evaluate how reconstruction algorithms and lesion radioactivity levels affect PET image quality and quantitative accuracy across three different PET systems. Materials and Methods: A NEMA phantom was filled with 18F and scanned by one PET/MRI and two PET/CT systems with sphere-to-background concentration ratio (SBR) of 2:1, 4:1, or 10:1. PET images were reconstructed with OSEM or BPL with TOF. The number of iterations and β-values were varied, while the matrix size, number of subsets, and filter size remained constant. Contrast recovery (CR) and background variability (BV) were measured in images. Results: CR increased with increased sphere size and SBR. CR and BV decreased with increased β for the 10mm sphere. Increased number of iterations in OSEM showed increased BV with limited variation in CR. BPL gave higher CR and lower BV values than OSEM. The optimal reconstruction was BPL with β between 150 and 350, where BPL was available, and OSEM with two iterations and 21 subsets for the PET/CT without BPL. Conclusion: BPL outperforms OSEM, and SBR significantly influences tracer uptake quantification in small lesions. Future studies should explore the clinical implications of these findings on diagnosis, staging, prognosis, and treatment follow-up.

In this paper, we explore a novel method for tomographic image reconstruction in the field of SPECT imaging. Deep Learning methodologies and more specifically deep convolutional neural networks (CNN) are employed in the new reconstruction method, which is referred to as "CNN Reconstruction - CNNR". For training of the CNNR Projection data from software phantoms were used. For evaluation of the efficacy of the CNNR method, both software and hardware phantoms were used. The resulting tomographic images are compared to those produced by filtered back projection (FBP) [1], the "Maximum Likelihood Expectation Maximization" (MLEM) [1] and ordered subset expectation maximization (OSEM) [2].

Effects of attenuation correction and reconstruction method on PET activation studies

The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal-to-noise ratio on images and more accurate quantitation than ordered subset-expectation maximization (OSEM). The reconstruction parameter (β) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal β value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18 F-fluoro-2-deoxy-D-glucose ([18 F]FDG) and 11 C-labeled Pittsburg compound B ([11 C]PiB). Images generated from Hoffman 3D brain and cylindrical phantoms were acquired using a Discovery PET/computed tomography (CT) 710 and reconstructed using OSEM+time-of-flight (TOF) under clinical conditions and BPL+TOF (β=20-1000). Contrast was calculated from images generated by the Hoffman 3D brain phantom, and noise and uniformity were calculated from those generated by the cylindrical phantom. Five cognitively healthy controls and five patients with Alzheimer disease were assessed using [18 F]FDG and [11 C]PiB PET to validate the findings from the phantom study. The β values were restricted by the findings of the phantom study, then one certified nuclear medicine physician and two certified nuclear medicine technologists visually determined optimal β values by scoring the quality parameters of image contrast, image noise, cerebellar stability, and overall image quality of PET images from 1 (poor) to 5 (excellent). The contrast in BPL satisfied the Japanese Society of Nuclear Medicine (JSNM) criterion of ≥55% and exceeded that of OSEM at ranges of β=20-450 and 20-600 for [18 F]FDG and [11 C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when β=150-1000 and 400-1000 for [18 F]FDG and [11 C]PiB, respectively. The phantom study restricted the ranges of β values to 100-300 and 300-500 for [18 F]FDG and [11 C]PiB, respectively. The BPL scores for gray-white matter contrast and image noise, exceeded those of OSEM in [18 F]FDG and [11 C]PiB images regardless of β values. Visual evaluation confirmed that the optimal β values were 200 and 450 for [18 F]FDG and [11 C]PiB, respectively. The BPL achieved better image contrast and less image noise than OSEM, while maintaining quantitative standardized uptake value ratios (SUVR) due to full convergence, more rigorous noise control, and edge preservation. The optimal β values for [18 F]FDG and [11 C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal β values in BPL for brain PET imaging.

The aim of this work was to develop a rigorous evaluation methodology to assess performance of different acquisition and processing methods for variable patient sizes in the context of lesion detection in whole-body (18)F-FDG PET. Fifty-nine bed positions were acquired in 32 patients in 2-dimensional (2D) and 3-dimensional (3D) modes 1-4 h after (18)F-FDG injection (740 MBq) using a BGO PET scanner. Three spheres (1.0-, 1.3-, and 1.6-cm diameter) containing (68)Ge were also imaged separately in air, at locations corresponding to possible lesion sites in 2D and 3D (590 targets per condition). Each bed position was acquired for 7 min in 2D and 6 min in 3D and corrected for randoms using delayed window randoms subtraction (DWS) or randoms variance reduction (RVR). Sphere sinograms were attenuated using the 2D or 3D attenuation map derived from the transmission scan of the patient, after scaling 2D and 3D sinograms with identical factors to ensure marginal detectability. Resulting 2D sinograms were reconstructed with filtered backprojection (FBP) and ordered-subsets expectation maximization (OSEM) without any scatter or attenuation correction (FBP-NATS and OSEM-NATS) or corrected for scatter and attenuation and reconstructed using FBP (FBP-ATT) or attenuation-weighted OSEM (AWOSEM). 3D sinograms were processed identically after Fourier rebinning. Next, reconstructed volumes were compared on the basis of performance of a 3-channel Hotelling observer (CHO-SNR [SNR is signal-to-noise ratio]) in detecting the presence of a sphere of unknown size on an anatomic background while modeling observer noise. The noise equivalent count (NEC) rate was computed in 2D and 3D for 3 different phantoms sizes (40, 60, and 95 kg) and compared with lesion detection SNR. 3D imaging yielded better lesion detectability than 2D (P < 0.025, 2-tailed paired t test) in patients of normal size (body mass index [BMI] < or = 31). However, 2D imaging yielded better lesion detectability than 3D in large patients (BMI > 31), as 3D performance deteriorated in large patients (P < 0.05). 2D and 3D yielded similar results for different lesion sizes. CHO-SNR were 40% greater for AWOSEM, FBP-ATT, and FBPNAT than for OSEM (P < 0.05), and AWOSEM yielded significantly better lesion detectability than did FBP. In all patients, RVR yielded a systematic improvement in CHO-SNR over DWS in both 2D and 3D. radicalNEC was characterized by a behavior similar to that of SNR(CHO) for the 3 different phantom sizes considered in this study.

Standardised Uptake Values (SUVs) are widely used in positron emission tomography (PET) as a semi-quantitative index of fluorine-18 labelled fluorodeoxyglucose uptake. The objective of this study was to investigate any bias introduced in the calculation of SUVs as a result of employing ordered subsets-expectation maximisation (OSEM) image reconstruction and segmented attenuation correction (SAC). Variable emission and transmission time durations were investigated. Both a phantom and a clinical evaluation of the bias were carried out. The software implemented in the GE Advance PET scanner was used. Phantom studies simulating tumour imaging conditions were performed. Since a variable count rate may influence the results obtained using OSEM, similar acquisitions were performed at total count rates of 34kcps and 12kcps. Clinical data consisted of 100 patient studies. Emission datasets of 5 and 15min duration were combined with 15-, 3-, 2- and 1-min transmission datasets for the reconstruction of both phantom and patient studies. Two SUVs were estimated using the average (SUVavg) and the maximum (SUVmax) count density from regions of interest placed well inside structures of interest. The percentage bias of these SUVs compared with the values obtained using a reference image was calculated. The reference image was considered to be the one produced by filtered backprojection (FBP) image reconstruction with measured attenuation correction using the 15-min emission and transmission datasets for each phantom and patient study. A bias of 5%-20% was found for the SUVavg and SUVmax in the case of FBP with SAC using variable transmission times. In the case of OSEM with SAC, the bias increased to 10%-30%. An overall increase of 5%-10% was observed with the use of SUVmax. The 5-min emission dataset led to an increase in the bias of 25%-100%, with the larger increase recorded for the SUVmax. The results suggest that OSEM and SAC with 3 and 2min transmission may be reliably used to reduce the overall data acquisition time without compromising the accuracy of SUVs.

In cerebral blood flow tests using N-Isopropyl-p-[123I] Iodoamphetamine "I-IMP, quantitative results of greater accuracy than possible using the autoradiography (ARG) method can be obtained with attenuation and scatter correction and image reconstruction by filtered back projection (FBP). However, the cutoff frequency of the preprocessing Butterworth filter affects the quantitative value; hence, we sought an optimal cutoff frequency, derived from the correlation between the FBP method and Xenon-enhanced computed tomography (XeCT)/cerebral blood flow (CBF). In this study, we reconstructed images using ordered subsets expectation maximization (OSEM), a method of successive approximation which has recently come into wide use, and also three-dimensional (3D)-OSEM, a method by which the resolution can be corrected with the addition of collimator broad correction, to examine the effects on the regional cerebral blood flow (rCBF) quantitative value of changing the cutoff frequency, and to determine whether successive approximation is applicable to cerebral blood flow quantification. Our results showed that quantification of greater accuracy was obtained with reconstruction employing the 3D-OSEM method and using a cutoff frequency set near 0.75-0.85 cycles/cm, which is higher than the frequency used in image reconstruction by the ordinary FBP method.

To characterize ordered-subset expectation maximization algorithm with a fixed 3D Gauss post-reconstruction filtering (OSEM) in 99mTc SPECT as for noise, contrast and spatial resolution with varying number of subset and iteration and to compare OSEM with an optimized set of parameters, with filtered backprojection (FBP) with filter parameters typical of brain and myocardial SPECT, both with and without Chang's method of attenuation correction (AC). SPECT images of a Jaszczak phantom with cold rod inserts, hot and cold spheres and capillary line sources were acquired. Different background activity concentrations of the phantom were simulated as well as different lesion-to-background activity ratios. OSEM reconstructions were halted after 5, 10 and 15 iterations using 4, 8 and 16 subsets. The effect of subset and iteration number over noise is additive: thus, it is possible to define an EM-equivalent iteration number that indicates the product between the subset and the iteration numbers. Noise increases linearly with increasing EM-equivalent iteration number. For each level of nominal contrast, the measured contrast after OSEM shows a little increase with increasing iteration number and saturates after 80 EM-equivalent iterations. The application of AC leads to diminished contrast values both in FBP and OSEM. The contrast of cold lesions after OSEM increases with increasing number of EM-equivalent iteration number: after 80 iterations the contrast values with OSEM overtake the ones obtained with FBP; contrast values diminished as background concentration raised. Resolution values did not change with increasing EM-equivalent iteration number and were higher than those obtained with FBP. The major findings of the present work are the demonstration of additivity of subset and iteration in OSEM over noise, with the possibility of defining an EM equivalent iteration number, and the superiority of OSEM with respect to FBP in terms of spatial resolution.